Technical Field
Embodiments of the present disclosure relate to the field of remote sensing, deep learning, and object detection.
Description of the Related Art
Structural and geospatial data are valuable in areas such as, for example, real estate transaction, planning, and/or insurance. Non-limiting examples of the structural and geospatial data include the following: the area of real property including land and/or buildings; the square footage of a building; the roof size and/or type; the presence of a pool and its size and/or location; and the presence of trees and its type, size, and/or location.
Traditionally, the structural and geospatial information can be obtained by (1) manually checking real estate records from relevant agencies; or (2) manually surveying the underlying real properties. These traditional methods suffer from a number of drawbacks and deficiencies. First, the records can be out of date, missing, or destroyed. Second, the manual checking and surveying are labor intensive and costly. Third, surveying area such as the roof of a building or the crown of a tree can be dangerous.
Therefore, there is a need in the art to provide systems and methods for obtaining structural and geospatial data that overcome these drawbacks and deficiencies.